Modeling Incomplete Longitudinal Data

This article presents a review of popular parametric, semiparametric and ad-hoc approaches for analyzing incomplete longitudinal data

Goal striving and well-being in sport: the role of contextual and personal motivation

This investigation sought to clarify mixed results in the literature exploring coach behaviors, basic psychological needs, goal motivation, and well- and ill-being. Regional level team sport athletes (N = 241) completed questionnaires on the aforementioned variables at the beginning of the season. A subsample (n = 70) provided saliva samples to assess physical ill-being. At the end of the season, athletes (n = 98) reported their goal motivation and attainment. Structural equation modeling demonstrated that coach behaviors were related to needs satisfaction and thwarting, which were related to autonomous and controlled goal motives respectively. Autonomous motives were related to well- and ill-being; controlled motives were only related to ill-being. Over time, only end-of-season autonomous goal motives were related to goal attainment. The findings provide an insight into how coaches can facilitate optimum goal striving and well-being in their athletes

Inheritances, Health and Death

We examine how wealth shocks, in the form of inheritances, affect the mortality rates, health status and health behaviors of older adults, using data from eight waves of the Health and Retirement Survey (HRS). Our main finding is that bequests do not have substantial effects on health, although some improvements in quality-of-life are possible. This absence occurs despite increases in out-of-pocket (OOP) spending on health care and in the utilization of medical services, especially discretionary and non-lifesaving types such as dental care. Nor can we find a convincing indication of changes in lifestyles that offset the benefits of increased medical care. Inheritances are associated with higher alcohol consumption, but with no change in smoking or exercise and a possible decrease in obesity.

National Time Accounting: The Currency of Life

This monograph proposes a new approach for measuring features of society’s subjective well-being, based on time allocation and affective experience. We call this approach National Time Accounting (NTA). National Time Accounting is a set of methods for measuring, comparing and analyzing how people spend and experience their time -- across countries, over historical time, or between groups of people within a country at a given time. The approach is based on evaluated time use, or the flow of emotional experience during daily activities. After reviewing evidence on the validity of subjective well-being measures, we present and evaluate diary-based survey techniques designed to measure individuals’ emotional experiences and time use. We illustrate NTA with: (1) a new cross-sectional survey on time use and emotional experience for a representative sample of 4,000 Americans; (2) historical data on the amount of time devoted to various activities in the United States since 1965; and (3) a comparison of time use and wellbeing in the United States and France. In our applications, we focus mainly on the Uindex, a measure of the percentage of time that people spend in an unpleasant state, defined as an instance in which the most intense emotion is a negative one. The U-index helps to overcome some of the limitations of interpersonal comparisons of subjective well-being. National Time Accounting strikes us as a fertile area for future research because of advances in subjective measurement and because time use data are now regularly collected in many countries.

Predicting Student Success in a Self-Paced Mathematics MOOC

abstract: While predicting completion in Massive Open Online Courses (MOOCs) has been an active area of research in recent years, predicting completion in self-paced MOOCS, the fastest growing segment of open online courses, has largely been ignored. Using learning analytics and educational data mining techniques, this study examined data generated by over 4,600 individuals working in a self-paced, open enrollment college algebra MOOC over a period of eight months. Although just 4% of these students completed the course, models were developed that could predict correctly nearly 80% of the time which students would complete the course and which would not, based on each student’s first day of work in the online course. Logistic regression was used as the primary tool to predict completion and focused on variables associated with self-regulated learning (SRL) and demographic variables available from survey information gathered as students begin edX courses (the MOOC platform employed). The strongest SRL predictor was the amount of time students spent in the course on their first day. The number of math skills obtained the first day and the pace at which these skills were gained were also predictors, although pace was negatively correlated with completion. Prediction models using only SRL data obtained on the first day in the course correctly predicted course completion 70% of the time, whereas models based on first-day SRL and demographic data made correct predictions 79% of the time.Dissertation/ThesisDoctoral Dissertation Educational Technology 201

Essays on Entrepreneurship

My papers have been focused on topics around entrepreneurship. From a micro perspective, my research adds to the still sparse literature on the entrepreneurial decisions within a household framework; while from a macro perspective, my research investigates the recent declining entrepreneurship in the United States during the past two decades. I start in Chapter 2 with the empirical finding that married people are more likely to be entrepreneurs than their single counterparts. I identify a causal effect that marriage increases entrepreneurship by employing a recent marriage policy reform in Australia as a natural experiment. The 2008 federal policy reform requires de facto couples (similar to the common-law marriage) and married couples to be treated equally regarding divorce or separation procedure in all states. I focus on two major states in Australia: Queensland which already had a similar law in place, and New South Wales which had no such legislation prior to the 2008 reform. Using the Household, Income and Labour Dynamics in Australia survey data for the years 2001 to 2015, I demonstrate that the policy reform has a positive effect on marriage through a difference-in-difference approach. By using the policy reform as an instrument variable, I show that marriage can increase the likelihood to be an entrepreneur by 7.96% for men and 1.19% for women. However, this causal effect is not consistent with the hypothesis from the family-insurance incentive, since I find a high rate of spouses both being entrepreneurs. Instead, I show that this causal effect is driven by the commitment to a marital relationship, which facilitates household specialization and joint entrepreneurship. Chapter 3 investigates the downward trend of U.S. self-employment rate as observed in the last two decades. Using data from the Current Population Survey Merged Outgoing Rotation Groups (CPS-ORG), I have decomposed this decline by gender, business incorporation status, industry, and entry/exit employment dynamic. Both the downward trend of non-incorporated businesses and the increasing exiting-rate of self-employment are recognized to be the primary causes of this decline. I have proposed an approach with Probit models to evaluate the net effect of intertwined determinants and demonstrated that many variables such as age and education have affected self-employment tendency differently for men and women. Moreover, through Blinder-Oaxaca decomposition, I have shown that the changing demographic factors could have contributed to an increase in self-employment by 11.9\%; while changes in the effects of these determinants have resulted in a counterfactual decline in self-employment by 30.2%. Furthermore, I have analyzed the effect of real wage on self-employment entry as well as the change in this effect over time. Overall, this research provides insights into the future of entrepreneurship and informs economic policymaking

Human Resource Management and Productivity

In this chapter we examine the relationship between Human Resource Management (HRM) and productivity. HRM includes incentive pay (individual and group) as well as many nonpay aspects of the employment relationship such as matching (hiring and firing) and work organization (e.g. teams, autonomy). We place HRM more generally within the literature on management practices and productivity. We start with some facts on levels and trends of both HRM and productivity and the main economic theories of HRM. We look at some of the determinants of HRM - risk, competition, ownership and regulation. The largest section analyses the impact of HRM on productivity emphasizing issues of methodology, data and results (from micro-econometric studies). We conclude briefly with suggestions of avenues for future frontier work.human resource management, productivity, personnel economics

Profiles of Academic Commitment

Tinto (1993) found that only 15-25% of students who dropped out of college did so due to academic failure, while the reasons for leaving among the remaining group of students who dropped out were unknown. This suggests that the majority of students who drop out of college are likely doing so for reasons other than academic struggles. Researchers have suggested that individuals who are committed to their major are more likely to obtain a bachelor’s degree (Bowling, Beehr, & Lepisto, 2006; Den Hartog & Belschak, 2007; Duffy, Dik, & Steger, 2011; Goulet & Singh, 2002; Landrum & Mulcock, 2007), indicating that academic major commitment is a highly important aspect of academic persistence. The purpose of the current study was to investigate commitment profile types of undergraduate students and relationships between these profiles and important academic outcomes (e.g., persistence, mental health). Results revealed a seven profile solution with each group relating uniquely to important outcomes for college students (i.e., retention, mental health, performance, and adjustment). Particularly, it was found that those with a mid-level or flat profile (i.e., mid level reports of commitment) reported greater intention to quit school, higher mental health problems and poorer adjustment. However, those with high affective and university commitment reported decreased intention of quitting, lower mental health concerns, better adjustment, and higher GPA. Other profile relationships and implications of these results are discussed. Masters thesis: http://aquila.usm.edu/masters_theses/33

From procrastination to engagement? An experimental exploration of the effects of an adaptive virtual assistant on self-regulation in online learning

Compared to traditional classroom learning, success in online learning tends to depend more on the learner’s skill to self-regulate. Self-regulation is a complex meta-cognitive skill set that can be acquired. This study explores the effectiveness of a virtual learning assistant in terms of (a) developmental, (b) general compensatory, and (c) differential compensatory effects on learners’ self-regulatory skills in a sample of N = 157 online learners using an experimental intervention-control group design. Methods employed include behavioural trace data as well as self-reporting measures. Participants provided demographic information and responded to a 24-item self-regulation questionnaire and a 20-item personality trait questionnaire. Results indicate that the adaptive assistance did not lead to substantial developmental shifts as captured in learners’ perceived levels of self-regulation. However, various patterns of behavioural changes emerged in response to the intervention. This suggests that the virtual learning assistant has the potential to help online learners effectively compensate for deficits (in contrast to developmental shifts) in self-regulatory skills that might not yet have been developed

Three Essays on Partial Identification for Applied Health Economics

This dissertation consists of three chapters which explore the usefulness of partial identification methods for estimating treatment effects in applied health economics research. Each one applies the methodology to different settings in which establishing causality has traditionally been difficult, and seeks to demonstrate when a bounding approach can—and cannot—aid researchers in learning about causal relationships.The first chapter studies the Housing Choice Voucher program in the United States and estimates bounds on the effect that receiving this form of housing assistance has on self-reported health status and the likelihood of hospitalization within the eligible population of renters. The second chapter aims to understand the relationship between mental health and labor market outcomes. We bound the impact depressive symptom severity has on both the probability of employment and on earnings. The third chapter provides a thorough exposition of the bounding strategy used throughout the dissertation and examines how genetic data might be used in the framework to study questions of public health interest. We demonstrate the latter by estimating bounds on the causal effect of both education and body mass index on mental health